LTX2.3-10Eros

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What LTX2.3-10Eros is

GGUF Version of LTX2.3-10Eros for ComfyUI Original model Link: https://huggingface.co/TenStrip/LTX2.3-10Eros Watch us at Youtube: @VantageWithAI - For v1.2 follow this link https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.2-GGUF - For v1.3 follow this link https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.3-GGUF - For v1.4 follow this link https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.4-GGUF - For v1.5 follow this link https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.5-GGUF 10 Eros Nodes: https://github.com/TenStrip/10S-Comfy-nodes Reliant on https://huggingface.co/SulphurAI/Sulphur-2-base This is a different merge attempt for ideal I2V use. It uses layer scaled merges of different steps, it's not a straight weight merge. It behaves much nicer than lora load and respects prompt. Prompt should be enhanced, LTX has very little self reasoning and input when it is conditioned, first frame and all following motions, evolutions, and audio must be commanded-you will get nothing if you don't ask it. !!! Larger distilled Loras will harm the model's fine tune, try the condsafe ones: https://huggingface.co/TenStrip/LTX2.3DistilledLora1.1Experiments/tree/main For prompt enhancement, try this foreword in Grok or Uncensored LLM: Generate a video scene script with a description based on the attached image for an LLM that has a tokenizer that uses interleaved attention to support long-context understanding that is fed into a multimodal video model. Strict specification, follow up to the word: No timestamps. No unnecessary embellishment. Output only plain English text and make it a copy box. First, describe the image initial scene in concise natural language; subject(s), subject(s) appearance, subject(s) composition and pose, background, and context. Next, formulate a naturally evolving scenario that would take place describing every moving body part, composition change, and manipulation from the uploaded initial frame that would be reflected in the video models post-latent evolution output. If the image is explicit or sexual in nature, use full anatomical terminology and spice it up slightly with visually representable erotic themes. Center the prompt around t

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How video models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys ltx2-3-10eros for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (ltx2-3-10eros below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"ltx2-3-10eros","prompt":"a drone shot over a forest"}'

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Commercial licence needed

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